The present invention relates to a method of assisting the detection of breast cancer.
Diagnostic imaging, such as ultrasound imaging or mammography, or palpation is routinely performed as a diagnostic test for breast cancer. However, it is reported that some cases of breast cancer are missed by those test methods, and stage 0 breast cancer preceding tumor mass formation is also not detectable at all by the test methods.
On the other hand, methods in which the abundance of microRNA (hereinafter referred to as “miRNA”) in blood is used as an index to detect breast cancer have been proposed (Patent Documents 1 to 3).
As described above, various miRNAs have been proposed as indexes for the detection of breast cancer and, needless to say, it is advantageous if breast cancer can be detected with higher accuracy.
Thus, an object of the present invention is to provide a method of assisting the detection of breast cancer which assists in highly accurate detection of breast cancer.
As a result of intensive study, the inventors newly found miRNAs, isoform miRNAs (isomiRs), transfer RNA fragments (tRFs), and non-coding RNA fragments (RRNAs, snoRNAs, LincRNAs) which increase or decrease in abundance in breast cancer, and discovered that use of these as indexes enables highly accurate detection of breast cancer, to thereby complete the present invention.
That is, the present invention provides the following:
(1) A method of assisting the detection of breast cancer, using as an index the abundance of at least one of miRNAs, isoform miRNAs (isomiRs), precursor miRNAs, transfer RNA fragments (tRFs), or non-coding RNA fragments (RRNAs, snoRNAs, or LincRNAs) contained in a test sample isolated from a living body, whose nucleotide sequence is represented by any one of SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, 1, 14, 27, 40, 25, 12, 160, 3 to 11, 13, 16 to 20, 29, 35 to 39, 42 to 150, 153 to 159, and 161 to 269, wherein a higher abundance of at least one of the miRNAs, isomiRs, precursor miRNAs, transfer RNA fragments, or non-coding RNA fragments whose nucleotide sequence is represented by any one of SEQ ID NOs: 1 to 19, 27, 28, 34 to 51, 74, 76, 77, 80 to 84, 96, 101 to 104, 115 to 122, 125, 128, 134 to 139, 151, 152, 159 to 165, 168, 169, 174, and 175 to 199 than that of healthy subjects or a lower abundance of at least one of the miRNAs, isomiRs, precursor miRNAs, transfer RNA fragments, or non-coding RNA fragments whose nucleotide sequence is represented by any one of SEQ ID NOs: 20 to 26, 29 to 33, 52 to 54, 56 to 73, 75, 78 to 79, 85 to 95, 97 to 100, 105 to 114, 123, 124, 126, 127, 129 to 133, 140 to 150, 153 to 158, 166, 167, 170 to 173, and 200 to 269 than that of healthy subjects indicates a higher likelihood of having breast cancer.
(2) The method according to (1), wherein the abundance of at least one of miRNAs, isoform miRNAs (isomiRs), or transfer RNA fragments (tRFs) whose nucleotide sequence is represented by any one of SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, 1, 14, 27, 40, 25, 12, 160, 3 to 11, 13, 16 to 20, 29, 35 to 39, 42 to 150, 153 to 159, and 161 to 174 is used as an index.
(3) The method according to (1), wherein the abundance of at least one of miRNAs, isomiRs, precursor miRNAs, transfer RNA fragments, or non-coding RNA fragments whose nucleotide sequence is represented by any one of SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, 1, 14, 27, 40, 25, 12, 160, 3 to 11, 13, 16, 20, 27, 29, 37 to 39, 41, 43, 45, 47 to 52, 56, 60, 66, 82, 86, 90 to 92, 107, 111, 112, 126, 127, 130, 137, 158, 161, 162, 173, and 175 to 265 is used as an index.
(4) The method according to (3), wherein the abundance of at least one of miRNAs, isomiRs, precursor miRNAs, or transfer RNA fragments whose nucleotide sequence is represented by any one of SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, 1, 14, 27, 40, 25, 12, 160, 3 to 11, 13, 16, 20, 27, 29, 37 to 39, 41, 43, 45, 47 to 52, 56, 60, 66, 82, 86, 90 to 92, 107, 111, 112, 126, 127, 130, 137, 158, 161, 162, and 173 is used as an index.
(5) The method according to (4), wherein the abundance of at least one of isomiRs or precursor miRNAs whose nucleotide sequence is represented by any one of SEQ ID NOs: 3 to 9 is used as an index.
(6) The method according to (2), wherein the abundance of at least one of miRNAs, isomiRs, precursor miRNAs, or transfer RNA fragments whose nucleotide sequence is represented by any one of SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, 1, 14, 27, 40, 25, 12, and 160 is used as an index.
(7) The method according to (6), wherein the abundance of at least one of isomiRs or transfer RNA fragments whose nucleotide sequence is represented by SEQ ID NO: 152, 151, 15, 40, 41, 1, or 14 is used as an index.
(8) The method according to (2), wherein the abundance of at least one of isomiRs or transfer RNA fragments whose nucleotide sequence is represented by any one of SEQ ID NOs: 2, 21, 22, 23, 24, 26, 31 to 33, and 55 is used as an index.
(9) The method according to (2), comprising measuring the abundance ratio of isoforms (isomiRs) of miR-150-5p (SEQ ID NO: 83) and/or miR-26b-5p (SEQ ID NO: 126) to the same microRNA(s) in the mature miRNA form contained in serum or plasma isolated from a living body (where “the abundance of isoforms (isomiRs)” refers to the total abundance of sequences in which 1 to 5 nucleotides are deleted from or added to the 3′ or 5′ end of a mature miRNA), wherein a higher abundance ratio than that of healthy subjects indicates a higher likelihood of having breast cancer.
(10) The method according to (2), comprising measuring the abundance ratio of isoforms (isomiRs) of miR-93-5p (SEQ ID NO: 155) and/or miR-17-5p (SEQ ID NO: 282) to the same microRNA(s) in the mature miRNA form contained in serum or plasma isolated from a living body (where “the abundance of isoforms (isomiRs)” refers to the total abundance of sequences in which 1 to 5 nucleotides are deleted from or added to the 3′ or 5′ end of a mature miRNA), wherein a lower abundance ratio than that of healthy subjects indicates a higher likelihood of having breast cancer.
By the method of the present invention, breast cancer can be highly accurately and yet conveniently detected. Thus, the method of the present invention will greatly contribute to the detection of breast cancer.
As described above, the abundance of a particular molecule selected from miRNAs, isomiRs, precursor miRNAs, transfer RNA fragments, or non-coding RNA fragments (hereinafter sometimes referred to as “miRNAs or the like” for convenience) contained in a test sample isolated from a living body is used as an index in the method of the present invention. These miRNAs or the like themselves are known, and the nucleotide sequences thereof are as shown in Sequence Listing. The list of miRNAs or the like used in the method of the present invention is presented in Table 1.
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_tRNA-
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_tRNA
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA
Homo_sapiens_tRNA-
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-Gly-
Homo_sapiens_tRNA-Gly-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo sapiens tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Homo_sapiens_tRNA-
Among those miRNAs or the like, miRNAs or the like whose nucleotide sequences are represented by SEQ ID NOs: 1 to 33, 56 to 173, and 175 to 269 (for example, “a miRNA or the like whose nucleotide sequence is represented by SEQ ID NO: 1” is hereinafter sometimes referred to simply as “a miRNA or the like represented by SEQ ID NO: 1” or “one represented by SEQ ID NO: 1” for convenience) are present in serum, and those represented by SEQ ID NOs: 34 to 55, and 174 are present in exosomes in serum.
Many of those miRNAs or the like show the logarithm of the ratio of the abundance in serum or exosomes from patients with breast cancer to the abundance in serum or exosomes from healthy subjects (represented by “log FC,” which means the logarithm of FC (fold change) to base 2) is more than 0.585 in absolute value (that is, a ratio of not less than about 1.5 or not more than about 1/1.5), which is statistically significant (1-test; p<0.05).
The abundance of miRNAs or the like represented by SEQ ID NOs: 1 to 19, 27, 28, 34 to 51, 74, 76, 77, 80 to 84, 96, 101 to 104, 115 to 122, 125, 128, 134 to 139, 151, 152, 159 to 165, 168, 169, and 175 to 199 is higher in patients with breast cancer than in healthy subjects, while the abundance of miRNAs or the like represented by SEQ ID NOs: 20 to 26, 29 to 33, 52 to 54, 56 to 73, 75, 78 to 79, 85 to 95, 97 to 100, 105 to 114, 123, 124, 126, 127, 129 to 133, 140 to 150, 153 to 158, 166, 167, 170 to 173, and 200 to 269 is lower in patients with breast cancer than in healthy subjects.
Among those, the miRNAs or the like whose nucleotide sequences are represented by any of SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, 1, 14, 27, 40, 25, 12, 160, 3 to 11, 13, 16, 20, 27, 29, 37 to 39, 41, 43, 45, 47 to 52, 56, 60, 66, 82, 86, 90 to 92, 107, 111, 112, 126, 127, 130, 137, 158, 161, 162, 173, and 175 to 265 have a log FC value of not less than 1.5 in absolute value and thus function as indexes with especially high sensitivity, and are preferable.
Additionally, among these, even stage 0 breast cancer (that is, cancer which is at a stage when no tumor mass has been formed and is undetectable by diagnostic imaging or palpation) can be detected by a method in which the abundance of one represented by any one of SEQ ID NOs: 3 to 9 is used as an index, as specifically described in Examples below.
The accuracy of each cancer marker is indicated using the area under the ROC curve (AUC: Area Under Curve) as an index, and cancer markers with an AUC value of 0.7 or higher are generally considered effective. AUC values of 0.90 or higher, 0.97 or higher, 0.98 or higher, and 1.00 correspond to cancer markers with high accuracy, very high accuracy, even higher accuracy, and complete accuracy (with no false-positive and false-negative events), respectively. Thus, the AUC value of each cancer marker is likewise preferably 0.90, more preferably not less than 0.97, still more preferably not less than 0.98, yet more preferably not less than 0.99, and most preferably 1.00 in the present invention. Those whose nucleotide sequences are represented by SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, 1, 14, 27, 40, 25, 12, and 160 are preferable because of an AUC value of 0.97 or higher; among those, those represented by SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, and 1 are more preferable because of an AUC value of 0.98 or higher; those represented by SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, and 152 are most preferable because of an AUC value of 1.00.
Furthermore, the abundance of the miRNAs or the like whose nucleotide sequences are represented by SEQ ID NOs: 2, 21, 22, 23, 24, 26, 31 to 33, and 55 is zero in either cancer patients or healthy subjects, and use of those miRNAs or the like thus enables high accuracy detection, similarly to miRNAs or the like having an AUC value of 1.00 (most of the small RNAs also have an AUC value of 1.00).
The test sample is not specifically limited, provided that the test sample is a body fluid containing miRNAs; typically, it is preferable to use a blood sample (including plasma, serum, and whole blood). For those represented by SEQ ID NOs: 1 to 33, 56 to 173, and 175 to 265, which are present in serum, it is simple and preferable to use serum or plasma as a test sample. For those represented by SEQ ID NOs: 34 to 54, which are present in exosomes, it is preferable to use serum or plasma as a test sample, to extract total RNA from the exosomes contained therein, and to measure the abundance of each miRNA or the like. The method of extracting total RNA in serum or plasma is well known and is specifically described in Examples below. The method per se of extracting total RNA from exosomes in serum or plasma is known and is specifically described in more detail in Examples below.
The abundance of each miRNA or the like is preferably measured (quantified) using a next-generation sequencer. Any instrument may be used and is not limited to a specific type of instrument, provided that the instrument determines sequences, similarly to next-generation sequencers. In the method of the present invention, as specifically described in Examples below, use of a next-generation sequencer is preferred over quantitative reverse-transcription PCR (qRT-PCR) which is widely used for quantification of miRNAs, to perform measurements from the viewpoint of accuracy because miRNAs or the like to be quantified include, for example, isomiRs, in which only one or more nucleotides are deleted from or added to the 5′ and/or 3′ ends of the original mature miRNAs thereof, and which should be distinguished from the original miRNAs when measured. Briefly, though details will be described specifically in Examples below, the quantification method can be performed, for example, as follows. When the RNA content in serum or plasma is constant, among reads measured in a next-generation sequencing analysis of the RNA content, the number of reads for each isomiR or mature miRNA per million reads is considered as the measurement value, where the total counts of reads with human-derived sequences are normalized to one million reads. When the RNA content in serum or plasma is variable in comparison with healthy subjects due to a disease, miRNAs showing little abundance variation in serum and plasma may be used. In cases where the abundance of miRNAs or the like in serum or plasma is measured, at least one miRNA selected from the group consisting of let-7g-5p, miR-425-3p, miR-425-5p, miR-23a-3p, miR-484-5p, and miR-191-5p is preferably used as an internal control, which are miRNAs showing little abundance variation in serum and plasma.
The cut-off value for the abundance of each miRNA or the like for use in evaluation is preferably determined based on the presence or absence of a statistically significant difference (t-test; p<0.05, preferably p<0.01, more preferably p<0.001) from healthy subjects with regard to the abundance of the miRNA or the like. Specifically, the value of log2 read counts (the cut-off value) can be preferably determined for each miRNA or the like, for example, at which the false-positive rate is optimal (the lowest); for example, the cut-off values (the values of log2 read counts) for several miRNAs or the like are as indicated in Table 2. The cut-off values indicated in Table 2 are only examples, and other values may be employed as cut-off values as long as those values are appropriate to determine statistically significant difference. Additionally, the optimal cut-off values vary among different populations of patients and healthy subjects from which data is collected. However, a cut-off value may be set such that the cut-off value is within the range of, usually ±20%, particularly ±10%, from the cut-off value indicated in Table 2 or 3.
Additionally, as seen in Examples and Comparative Examples below, the abundance of a miRNA and that of each isomiR thereof are different between patients and healthy subjects, even among miRNAs or the like derived from the same archetype. For example, when miR-15a 5p is an archetype miRNA in Example 2 and Comparative Example 1 below, the log FC value of a miRNA (SEQ ID NO: 270) in Comparative Example 1 is 0, while the log FC value of an isomiR in the Mature-5′-sub type (SEQ ID NO: 2) in Example 2 is 5.67, indicating a predominantly higher abundance of the isomiR in patients with breast cancer. Thus, the measurement of the molecules represented by SEQ ID NO: 2 and SEQ ID NO: 270 in one patient can assist in breast cancer detection based on the abundance ratio thereof. Furthermore, Examples 85 to 88 (SEQ ID NOs: 85 to 88) are likewise isomiRs belonging to the miR-15a 5p family and each have different log FC values. Thus, the ratios between these values can be included into indexes to assist in more accurate detection. Because small differences in nucleotide sequence should be accurately distinguished, when the abundance of a certain miRNA and that of an isomiR thereof are measured, use of a next-generation sequencer is preferred over quantitative reverse-transcription PCR (qRT-PCR) which is typically used in miRNA measurement to perform measurements. Although no difference can be detected in the miRNA (SEQ ID NO: 270) in Comparative Example 1 which is a mature microRNA that can be detected by qRT-PCR, a significant difference can be found in Example 2 (SEQ ID NO:2) with the isomiR in the Mature-5′-sub type which can be detected by next-generation sequencers. Thus, using a next-generation sequencer is advantageous.
Each of the above miRNAs or the like is statistically significantly different in abundance between patients with breast cancer and healthy subjects, and may thus be used alone as an index. However, a combination of multiple miRNAs may also be used as an index, which can assist in more accurate detection of breast cancer.
Additionally, as specifically described in Examples below, the detection of breast cancer can also be assisted by measuring the abundance ratio of isoforms (isomiRs) of miR-150-5p (SEQ ID NO: 83) and/or miR-26b-5p (SEQ ID NO: 126) to the same microRNA(s) in the mature miRNA form contained in serum or plasma isolated from a living body (where “the abundance of isoforms (isomiRs)” refers to the total abundance of sequences in which 1 to 5 nucleotides are deleted from or added to the 3′ or 5′ end of a mature miRNA). In this case, a higher abundance ratio than that of healthy subjects indicates a higher likelihood of having breast cancer. This method shows a very high statistically significant difference (with a very small p-value) and is therefore considered as an accurate method.
Similarly, as specifically described in Examples below, the detection of breast cancer can also be assisted by measuring the abundance ratio of isoforms (isomiRs) of miR-93-5p (SEQ ID NO: 155) and/or miR-17-5p (SEQ ID NO: 282) to the same microRNA(s) in the mature miRNA form contained in serum or plasma isolated from a living body (where “the abundance of isoforms (isomiRs)” refers to the total abundance of sequences in which 1 to 5 nucleotides are deleted from or added to the 3′ or 5′ end of a mature miRNA). In this case, a lower abundance ratio than that of healthy subjects indicates a higher likelihood of having breast cancer. This method shows a very high statistically significant difference (with a very small p-value) and is therefore considered as an accurate method.
Moreover, a method of detecting the abundance of miRNAs or the like in a test sample from an individual suspected of having or affected with breast cancer is also provided.
That is, a method of detecting the abundance of at least one of miRNAs, isoform miRNAs (isomiRs), precursor miRNAs, transfer RNA fragments (tRFs), or non-coding RNA fragments (RRNAs, snoRNAs, or LincRNAs) whose nucleotide sequence is represented by any one of SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, 1, 14, 27, 40, 25, 12, 160, 3 to 11, 13, 16 to 20, 29, 35 to 39, 42 to 150, 153 to 159, 161 to 265 in a test sample from an individual suspected of having or affected with breast cancer is also provided, wherein the method includes the steps of:
collecting a blood sample from the individual; and
measuring the abundance of the RNA strand(s) in the blood sample by means of a next-generation sequencer or qRT-PCR;
wherein the abundance of at least one of the miRNAs, isomiRs, precursor miRNAs, transfer RNA fragments, or non-coding RNA fragments whose nucleotide sequence is represented by any one of SEQ ID NOs: 1 to 19, 27, 28, 34 to 51, 74, 76, 77, 80 to 84, 96, 101 to 104, 115 to 122, 125, 128, 134 to 139, 151, 152, 159 to 165, 168, 169, 174, and 175 to 199 is higher in patients than in healthy subjects, or the abundance of at least one of the miRNAs, isomiRs, precursor miRNAs, transfer RNA fragments, or non-coding RNA fragments whose nucleotide sequence is represented by any one of SEQ ID NOs: 20 to 26, 29 to 33, 52 to 54, 56 to 73, 75, 78 to 79, 85 to 95, 97 to 100, 105 to 114, 123, 124, 126, 127, 129 to 133, 140 to 150, 153 to 158, 166, 167, 170 to 173, and 200 to 265 is lower in patients than in healthy subjects.
Additionally, in cases where the detection of breast cancer is successfully achieved by the above-described method of the present invention, an effective amount of an anti-breast cancer drug can be administered to patients in whom breast cancer is detected, to treat the breast cancer. Examples of the anti-breast cancer drug can include Herceptin, trastuzumab, pertuzumab, trastuzumab emtansine-paclitaxel, docetaxel, vinorelbine, lapatinib, and capecitabine.
The present invention will be specifically described below by way of examples and comparative examples. However, the present invention is not limited to the examples below.
Serum samples from 109 patients with breast cancer and 72 healthy subjects were used. The numbers of patients with breast cancer at stage 0 and at stage 1 or later were 6 and 134, respectively.
Extraction of RNA in serum was performed using the miRNeasy Mini kit (QIAGEN).
1) Each frozen serum sample was thawed and centrifuged at 10,000 rpm for 5 minutes at room temperature to precipitate aggregated proteins and blood cell components.
2) To a new 1.5-mL tube, 200 μL of the supernatant was transferred.
3) To the tube, 1000 μL of the QIAzol Lysis Reagent was added and mixed thoroughly to denature protein components.
4) To the tube, 10 μL of 0.05 nM cel-miR-39 was added as a control RNA for RNA extraction, mixed by pipetting, and then left to stand at room temperature for 5 minutes.
5) To promote separation of the aqueous and organic solvent layers, 200 μL of chloroform was added to the tube, mixed thoroughly, and left to stand at room temperature for 3 minutes.
6) The tube was centrifuged at 12,000×g for 15 minutes at 4° C. and 650 μL of the upper aqueous layer was transferred to a new 2-mL tube.
7) For the separation of RNA, 975 μL of 100% ethanol was added to the tube and mixed by pipetting.
8) To a miRNeasy Mini spin column (hereinafter referred to as “column”), 650 μL of the mixture in the step 7 was transferred, left to stand at room temperature for 1 minute, and then centrifuged at 8000×g for 15 seconds at room temperature to allow RNA to be adsorbed on the filter of the column. The flow-through solution from the column was discarded.
9) The step 8 was repeated until the total volume of the solution of the step 7 was filtered through the column to allow all the RNA to be adsorbed on the filter.
10) To remove impurities attached on the filter, 650 μL of Buffer RWT was added to the column and centrifuged at 8000×g for 15 seconds at room temperature. The flow-through solution from the column was discarded.
11) To clean the RNA adsorbed on the filter, 500 μL of Buffer RPE was added to the column and centrifuged at 8000×g for 15 seconds at room temperature. The flow-through solution from the column was discarded.
12) To clean the RNA adsorbed on the filter, 500 μL of Buffer RPE was added to the column and centrifuged at 8000×g for 2 minutes at room temperature. The flow-through solution from the column was discarded.
13) To completely remove any solution attached on the filter, the column was placed in a new 2-mL collection tube and centrifuged at 10,000×g for 1 minute at room temperature.
14) The column was placed into a 1.5-mL tube and 50 μL of RNase-free water was added thereto and left to stand at room temperature for 1 minute.
15) Centrifugation was performed at 8000×g for 1 minute at room temperature to elute the RNA adsorbed on the filter. The eluted RNA was used in the following experiment without further purification and the remaining portion of the eluted RNA was stored at −80° C.
(3) Extraction of RNA from Exosomes
Exosomes in serum were isolated with the Total Exosome Isolation (from serum), a commercially available kit from Thermo Fisher Scientific, Inc. Extraction of RNA from the collected exosomes was performed using the miRNeasy Mini kit (trade name, manufactured by QIAGEN).
(4) Quantification of miRNAs or the Like
The quantification of miRNAs or the like was performed as follows. In cases where miRNAs or the like from, for example, two groups were quantified, extracellular vesicles (including exosomes) isolated by the same method were used to extract RNAs through the same method, from which cDNA libraries were prepared and then analyzed by next-generation sequencing. The next-generation sequencing analysis is not limited by a particular instrument, provided that the instrument determines sequences.
Specifically, the cut-off value and the AUC were calculated from measurement results as follows. The logistic regression analysis was carried out using the JMP Genomics 8 (trade name) to draw the ROC curve and to calculate the AUC. Moreover, the value corresponding to a point on the ROC curve which was closest to the upper left corner of the ROC graph (sensitivity: 1.0, specificity: 1.0) was defined as the cut-off value.
The results are presented in Table 2.
As seen in these results, the abundance of the miRNAs or the like represented by SEQ ID NOs: 1 to 19, 27, 28, 34 to 51, 74, 76, 77, 80 to 84, 96, 101 to 104, 115 to 122, 125, 128, 134 to 139, 151, 152, 159 to 165, 168, 169, 174, and 175 to 199 was significantly higher in the patients with breast cancer than in the healthy subjects, while the abundance of the miRNAs or the like represented by SEQ ID NOs: 20 to 26, 29 to 33, 52 to 54, 56 to 73, 75, 78 to 79, 85 to 95, 97 to 100, 105 to 114, 123, 124, 126, 127, 129 to 133, 140 to 150, 153 to 158, 166, 167, 170 to 173, and 200 to 265 was significantly lower in the patients with breast cancer than in the healthy subjects. It was indicated that breast cancer was able to be detected with higher accuracy by the method of the present invention (Examples 1 to 265), when compared with using, as indexes, miRNAs or the like (Comparative Examples 1 to 13) that are slightly different in length from those used in the method of the present invention. Moreover, most of the p-values determined by 1-test in Examples 1 to 265 were less than 0.05, indicating the effectiveness in detection of breast cancer.
Moreover, stage 0 breast cancer was also able to be detected by the methods in which those represented by SEQ ID NOs: 3 to 9 were used as indexes. Furthermore, those represented by SEQ ID NOs: 2, 21, 22, 23, 24, 26, 30, 31, 32, 33, 34, 152, 151, 15, 28, 41, 1, 14, 27, 40, 25, 12, and 160 have an AUC value of 0.97 or higher and are especially preferable. Furthermore, it was indicated that the abundance of the miRNAs or the like represented by SEQ ID NOs: 2, 21, 22, 23, 24, 26, 31 to 33, and 55 was zero in either cancer patients or healthy subjects, and use of those miRNAs or the like thus enabled high accuracy detection, similarly to use of miRNAs or the like having an AUC value of 1.00.
Similarly to Examples 1 to 269, the abundance of miR-150-5p (SEQ ID NO: 83) and miR-26b-5p (SEQ ID NO: 126) in the mature miRNA form (“mature” in Table 3) and the abundance of isoforms (isomiRs) of each of the miRNAs contained in serum were measured. In this respect, “the abundance of isoforms (isomiRs)” refers to the total abundance of sequences in which 1 to 5 nucleotides are deleted from or added to the 3′ or 5′ end of a mature miRNA. The abundance ratio between each miRNA and isoforms thereof was measured. The results are shown in Table 3 below.
Similarly to Examples 1 to 269, the abundance of miR-93-5p (SEQ ID NO: 155) and/or miR-17-5p (SEQ ID NO: 282) in the mature miRNA form (“mature” in Table 3) and the abundance of isoforms (isomiRs) of each of the miRNAs contained in serum were measured. In this respect, “the abundance of isoforms (isomiRs)” refers to the total abundance of sequences in which 1 to 5 nucleotides are deleted from or added to the 3′ or 5′ end of a mature miRNA. The abundance ratio between each miRNA and isoforms thereof was measured. The results are shown in Table 3 below.
As indicated in Table 3, a higher isomiR/mature miRNA ratio than that of healthy subjects in the measurement of miR-150-5p (SEQ ID NO: 83) and miR-26b-5p (SEQ ID NO: 126) indicated a higher likelihood of having breast cancer, while a lower isomiR/mature miRNA ratio than that of healthy subjects in the measurement of miR-93-5p (SEQ ID NO: 155) and miR-17-5p (SEQ ID NO: 282) indicated a higher likelihood of having breast cancer.
Number | Date | Country | Kind |
---|---|---|---|
2017-238811 | Dec 2017 | JP | national |
Filing Document | Filing Date | Country | Kind |
---|---|---|---|
PCT/JP2018/045936 | 12/13/2018 | WO | 00 |